Assessing SimCLIM climate model accuracy in projecting Southern Levantine basin air temperature trends up to 2100

This study evaluates the validity of forecasting air temperature ranges in 2100 using the SimCLIM climate projection model at spatial and temporal scales within the Southern Levantine basin. The model utilized historical air temperature data from 2000 to 2016, collected at seven southeastern Mediterranean stations, as well as 74 climate pattern ensembles integrated within SimCLIM. A combination of 40 global climate models (GCMs) and IPCC AR5 greenhouse gas emissions scenarios embedded in SimCLIM was employed to forecast mean, minimum, and maximum temperatures for 2100.The findings reveal that the average temperature increase in 2100, relative to the representative concentration pathways 2.6, 4.5, 6.0, and 8.5, will range between 0.8–1.17 °C, 1.48–2.0 °C, 2.1–3.8 °C, and 3.9–4.6 °C, respectively. Due to its acceptable accuracy, the SimCLIM model, incorporating 40 GCMs and 74 climate pattern ensembles, is highly recommended for forecasting future climate conditions. The model was evaluated using available temperature records in the study area, yielding a prediction percentage error of 2%, which strongly supports the use of SimCLIM.


Study area
The study area encompasses the Mediterranean coastline of Egypt, situated between 25° E and 34.5° E longitude and 30° N and 33° N latitude, within the southern Levantine sub-basin.This coastal region spans approximately 1000 km, stretching from Rafah to Sallum, as depicted in Fig. 1.It is categorized based on its geological and physiographic characteristics into four distinct sectors: the North Sinai coastal sector, which extends from Rafah to Port Said (180 km); the Nile Delta coastal sector, which stretches from Port Said to Alexandria (240 km); the Alexandria coastal sector, which ranges from Abu Qir Headland to Hammam (70 km); and the westernmost sector of the Egyptian Mediterranean coast, which extends for about 550 km from Hammam to Sallum.These divisions and geographic boundaries have been reported by Frihy and El-Sayed 16 and Abayazid et al. 17 .

Historical site air temperature data
Air temperature data were recorded at seven locations along the Egyptian Mediterranean coast.Site-specific data were sourced from the Global Historical Climatology Network (GHCN) daily dataset, which is maintained by the National Oceanic and Atmospheric Administration's National Climate Data Center.SimCLIM center acquired these data, as indicated in Table 1.The dataset covers the period from 1957 to 2016, with a focus on the years 2000 to 2016 for the analysis.

Cordex international database
The COordinated Regional Climate Downscaling EXperiment (CORDEX) is a framework supported by the World Climate Research Program (WCRP) that generates datasets of regional climate predictions for all continents worldwide.

Downscaling using SimCLIM and forecasting long-term temperature trends
Downscaling from GCMs Down-scaling mechanisms, including the pattern scaling technique, were employed with the SimCLIM model to process temperature data obtained from the CORDEX database and projected onto specific geographical locations.These selected locations correspond to the historical site data.Furthermore, air temperature forecasts will be generated from the base period (2000-2016) up to 2100, employing simple and direct descriptive statistics (minimum, mean, and maximum), with the selected Representative Concentration Pathways (RCPs) being 2.6, 4.5, 6.0, and 8.5.
As reported by Mitchell 18 , the pattern scaling technique depends on Eq. ( 1) where (V * ) is the anomaly in a variable (V ) for a particular box domain (i) , during period year (y) or months/season (j) for a selected forcing scenario (x) , the annual global anomaly of Tmean, which can be calculated by modelling the chosen forcing scenario is the scalar quantity (S) , the response value at each box domain node is the scalar quantity (z) , and the response pattern is given by (V ′).

Application of SimCLIM climate pattern on the historical site data
Climate models employ intricate patterns to simulate various components of the Earth's climate system, including temperature, precipitation, air circulation, and more.These patterns are constructed using mathematical formulae and scientific laws that govern the behavior of the Earth's atmosphere, oceans, land surfaces, and ice.In SimCLIM, specific climate model patterns will be applied to historical site data to illustrate temperature changes in the context of the Representative Concentration Pathways (RCPs) up to the year 2100, considering the base period from 2000 to 2016.Producing regional climate change patterns can be achieved through various approaches, such as statistical or dynamical downscaling.However, pattern scaling offers certain advantages over other techniques.Therefore, in this section, pattern scaling is also employed in the analysis.Some examples of the patterns used include CANESM2, CCSM4, CESM1-BGC, CESM1-CAM5, CMCC-CM, CMCC-CMS, CMCC-CM5, etc.

Model evaluation
Climate model evaluation is a crucial step in climate research.It assesses the efficacy of numerical climate models in simulating past, present, and future climatic conditions.This evaluation procedure aims to gauge how effectively these models reproduce observable climatic features, understand their limitations, and improve their accuracy.The simplest approach to model evaluation involves comparing model outputs with observational data and analyzing any discrepancies.Such comparisons require an understanding of the inherent flaws and (1) www.nature.com/scientificreports/uncertainties in the observational data, as reported by Flato et al. 19 and Randall et al. 20 .A more sophisticated evaluation method involves selecting a different future period from the one initially examined while using the same evaluation techniques.In this study, the SimCLIM model was assessed by calculating the percentage prediction error between two sets of outputs projected for the year 2040 based on two simulation scenarios: RCPs 2.6 and 8.5.The first set of outputs consists of downscaled data from 40 GCMs generated by SimCLIM, while the second set is derived from a pattern scaling method embedded in pattern ensembles and applied to SimCLIM measured dataset.The Port Said station was specifically selected for this evaluation.Before initiating the evaluation process, the mean temperature (Tmean) data from SimCLIM, originally sourced from GHCN, were compared with another set of Tmean data for the same period (2007-2016), as published in Kareem et al. 14 , Table 2.It should be noted that both stations are located 2 m above sea level and under similar conditions.They are 4.5 km apart, each owned by a different institution.Descriptive statistics were applied to the raw data to ensure its accuracy and compatibility, and it was found that the Port Said station is the best station to undergo the evaluation procedure.

Spatial distribution of air temperature
The spatial distribution of air temperature data was examined using historical data from seven geographical positions, representing the air temperature distribution from west to east along the Egyptian Mediterranean Sea during the study's base period (2000-2016).Monthly averages of Tmin, Tmean, and Tmax were selected as fundamental descriptive statistics to simplify the results (see Fig. 3).It is evident that during the winter months (December, January, February, and March), the lowest minimum temperatures are recorded at the Al Arish station, representing the North Sinai coastal region, ranging between 7.3 and 10.02 °C (Fig. 2a).Conversely, the adjacent coastal sector (the Nile Delta) experiences the highest minimum temperatures, particularly at Port Said and Baltim stations, where temperatures range from 14.4 to 10.5 °C (Fig. 2a).The highest maximum temperature during winter was observed at the Al Arish coastal station, reaching 23.1 °C (Fig. 2b).The average winter temperature varies from 11.37 in Alexandria to 17.29 °C in Port Said.Notably, temperatures increase in Alexandria when moving east and west from the middle sector (Fig. 2c).January stands out as the coldest month of the winter season overall.In the summer, maximum temperatures at the Al Arish station peaked at 33.1 °C, especially in August, followed by Sallum station in July, reaching up to 31.5 °C (Fig. 2b).These findings align with previous studies by Domroes and El-Tantawi 9 , Hasanean and Abdel Basset 21 , Kareem et al. 14 , and and Shaltout et al. 12,13 .

The change between the base period and 2100
Figures (36:38) show the estimation limits of the minimum, mean, and maximum temperature increase output from the middle climate sensitivity with respect to the base period and, according to RCPs 2.6, 4.5, 6.0, and 8.5 during 2100, downscaled from 74 pattern ensembles, are from west to east along the Egyptian Mediterranean coast.Relative to Tmin, they are as follows: 0.86:1.173°C, 1.48:1.79°C, 2.1:2.7 °C, and 3.9:4.2°C, respectively.

Discussion and conclusions
The SimCLIM model combined with 40 GCMs and 74 climate pattern ensembles collaborated by IPCC AR5 GHG emission scenarios predicts a dominant upward trend in air temperature for the year 2100 in the Egyptian Mediterranean coastal area, which is extremely compatible with previous studies concerned with temperature forecasting either at the global scale (Zittis 22 ) or at the regional scale (Nastos and Kapsomenakis 23 , Philandras et al. 24 , 25 ) where all agreed that there would be an upward tendency in the future relative to the air temperature.Furthermore, the positive temperature inclination projected in this research supports the temperature projection Also, during the autumn (October and November), the temperature varied from 17.58 °C at Sallum to 24.9 °C at Port Said, which shows an increase in the mean temperature from west to east.Relative to RCP 8.5, the increase in temperature will be up to 3.9 °C to 4.6 °C by 2100.Moreover, there were ups and downs in Tmin and Tmax in between sectors, but a general increase trend from west to west was confirmed by (Elbessa et al. 27 ) using the RegCM-SVN model.This model is highly recommended in the evaluation of future climate scenarios.
Global observations have noted fluctuations in extreme temperature markers 28,29 , which align with the unique temperature anomalies recorded at the Al Arish station.This station reports both the lowest minimum temperatures in winter and the highest maximum temperatures in winter.Several factors influence the climate of Al Arish, including microclimatic elements, such as its geographical location in the desert of the North Sinai Peninsula.It is just a few miles from the northern coastline and a short distance from a mountain range to the south.As a result, the area experiences specific meteorological phenomena, such as breezes, katabatic winds, and anabatic winds 26 .Additionally, this anomaly could be attributed to the influence of thermohaline circulation in the eastern Mediterranean and winter mixing typically observed in December-January.As reported by Menna et al. 30 , these factors affect the air above the sea.

Figure 1 .
Figure 1.The Egyptian Mediterranean coast with the locations of the stations marked by red circles.This image was created using Delft Dashboard (https:// publi cwiki.delta res.nl/ displ ay/ DDB/ Delft+ Dashb oard).

Figure 2 .
Figure 2. Monthly averages of the air temperature historical site data between 2000 and 2016.These graphs were created using Excel in the Microsoft Office Professional Plus 2016 package.

Figure 3 .
Figure 3. Averages of monthly minimum air temperatures according to the RCPs at Sallum.These graphs were created using Excel in the Microsoft Office Professional Plus 2016 package.

Figure 4 .
Figure 4. Averages of monthly minimum air temperatures according to the RCPs at Mersah Matruh.These graphs were created using Excel in the Microsoft Office Professional Plus 2016 package.

Figure 5 .
Figure 5. Averages of monthly minimum air temperatures according to the RCPs at Dabaa.These graphs were created using Excel in the Microsoft Office Professional Plus 2016 package.

Figure 6 .
Figure 6.Averages of monthly minimum air temperatures according to the RCPs at Alexandria.These graphs were created using Excel in the Microsoft Office Professional Plus 2016 package.

Figure 7 .
Figure 7. Averages of monthly minimum air temperatures according to the RCPs at Baltim.These graphs were created using Excel in the Microsoft Office Professional Plus 2016 package.

Figure 8 .
Figure 8. Averages of monthly minimum air temperatures according to the RCPs at Port Said.These graphs were created using Excel in the Microsoft Office Professional Plus 2016 package.

Figure 9 .Figure 10 .
Figure 9. Averages of monthly minimum air temperatures according to the RCPs at Al Arish.These graphs were created using Excel in the Microsoft Office Professional Plus 2016 package.

Figure 11 .
Figure 11.Distributions of the Projected seasonal and annual minimum air temperatures during 2100, according to RCP 4.5, along the Egyptian Mediterranean coast.The illustration was generated using SimCLIM v4.x for Desktop (SimCLIM AR5 (climsystems.com)).

Figure 12 .
Figure 12.Distributions of the Projected seasonal and annual minimum air temperatures during 2100, according to RCP 6.0, along the Egyptian Mediterranean coast.The illustration was generated using SimCLIM v4.x for Desktop (SimCLIM AR5 (climsystems.com)).

Figure 13 .
Figure 13.Distributions of the Projected seasonal and annual minimum air temperatures during 2100, according to RCP 8.5, along the Egyptian Mediterranean coast.The illustration was generated using SimCLIM v4.x for Desktop (SimCLIM AR5 (climsystems.com)).

Figure 14 .
Figure 14.Averages of monthly mean air temperatures according to the RCPs at Sallum.These graphs were created using Excel in the Microsoft Office Professional Plus 2016 package.

Figure 15 .
Figure 15.Averages of monthly mean air temperatures according to the RCPs at Mersah Matruh.These graphs were created using Excel in the Microsoft Office Professional Plus 2016 package.

Figure 16 .
Figure 16.Averages of monthly mean air temperatures according to the RCPs at Dabaa.These graphs were created using Excel in the Microsoft Office Professional Plus 2016 package.

Figure 17 .
Figure 17.Averages of monthly mean air temperatures according to the RCPs at Alexandria.These graphs were created using Excel in the Microsoft Office Professional Plus 2016 package.

Figure 18 .
Figure 18.Averages of monthly mean air temperatures according to the RCPs at Baltim.These graphs were created using Excel in the Microsoft Office Professional Plus 2016 package.

Figure 19 .
Figure 19.Averages of monthly mean air temperatures according to the RCPs at Port Said.These graphs were created using Excel in the Microsoft Office Professional Plus 2016 package.

Figure 20 .
Figure 20.Averages of monthly mean air temperatures according to the RCPs at Al Arish.These graphs were created using Excel in the Microsoft Office Professional Plus 2016 package.

Figure 21 .
Figure 21.Distributions of the Projected seasonal and annual mean air temperatures during 2100, according to RCP 2.6, along the Egyptian Mediterranean coast.The illustration was generated using SimCLIM v4.x for Desktop (SimCLIM AR5 (climsystems.com)).

Figure 22 .
Figure 22.Distributions of the Projected seasonal and annual mean air temperatures during 2100, according to RCP 4.5, along the Egyptian Mediterranean coast.The illustration was generated using SimCLIM v4.x for Desktop (SimCLIM AR5 (climsystems.com)).

Figure 23 .
Figure 23.Distributions of the Projected seasonal and annual mean air temperatures during 2100, according to RCP 6.0, along the Egyptian Mediterranean coast.The illustration was generated using SimCLIM v4.x for Desktop (SimCLIM AR5 (climsystems.com)).

Figure 24 .
Figure 24.Distributions of the Projected seasonal and annual mean air temperatures during 2100, according to RCP 8.5, along the Egyptian Mediterranean coast.The illustration was generated using SimCLIM v4.x for Desktop (SimCLIM AR5 (climsystems.com)).

Figure 25 .
Figure 25.Averages of monthly maximum air temperatures according to the RCPs at Sallum.These graphs were created using Excel in the Microsoft Office Professional Plus 2016 package.

Figure 26 .
Figure 26.Averages of monthly maximum air temperatures according to the RCPs at Mersah Matruh.These graphs were created using Excel in the Microsoft Office Professional Plus 2016 package.

Figure 27 .
Figure 27.Averages of monthly maximum air temperatures according to the RCPs at Dabaa.These graphs were created using Excel in the Microsoft Office Professional Plus 2016 package.

Figure 28 .
Figure 28.Averages of monthly maximum air temperatures according to the RCPs at Alexandria.These graphs were created using Excel in the Microsoft Office Professional Plus 2016 package.

Figure 29 .
Figure 29.Averages of monthly maximum air temperatures according to the RCPs at Baltim.These graphs were created using Excel in the Microsoft Office Professional Plus 2016 package.

Figure 30 .
Figure 30.Averages of monthly maximum air temperatures according to the RCPs at Port Said.These graphs were created using Excel in the Microsoft Office Professional Plus 2016 package.

Figure 31 .Figure 32 .
Figure 31.Averages of monthly maximum air temperatures according to the RCPs At al. Arish.These graphs were created using Excel in the Microsoft Office Professional Plus 2016 package.

Figure 33 .
Figure 33.Distributions of the Projected seasonal and annual maximum air temperatures during 2100, according to RCP 4.5, along the Egyptian Mediterranean coast.The illustration was generated using SimCLIM v4.x for Desktop (SimCLIM AR5 (climsystems.com)).

Figure 34 .
Figure 34.Distributions of the Projected seasonal and annual maximum air temperatures during 2100, according to RCP 6.0, along the Egyptian Mediterranean coast.The illustration was generated using SimCLIM v4.x for Desktop (SimCLIM AR5 (climsystems.com)).

Figure 35 .
Figure 35.Distributions of the Projected seasonal and annual maximum air temperatures during 2100, according to RCP 8.5, along the Egyptian Mediterranean coast.The illustration was generated using SimCLIM v4.x for Desktop (SimCLIM AR5 (climsystems.com)).

Figure 36 .
Figure 36.The change in average minimum temperature between the base period and 2100, according to RCPs, along the Egyptian Mediterranean coast.The illustration was generated using SimCLIM v4.x for Desktop (SimCLIM AR5 (climsystems.com)).

Figure 37 .
Figure 37.The Change in average mean temperature between the base period and 2100, according to RCPs, along the Egyptian Mediterranean coast.The illustration was generated using SimCLIM v4.x for Desktop (SimCLIM AR5 (climsystems.com)).

Figure 38 .
Figure 38.The Change in average Maximum temperature between the base period and 2100, according to RCPs, along the Egyptian Mediterranean coast.The illustration was generated using SimCLIM v4.x for Desktop (SimCLIM AR5 (climsystems.com)).

Table 1 .
The air temperature historical site data (HGCN) for seven locations along the Egyptian Mediterranean coastal area supported by SimCLIM center, from (2000:2016).